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How many words make a sample? Determining the minimum number of word tokens needed in connected speech samples for child speech assessment

Wren, Yvonne; Titterington, Jill; White, Paul

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Authors

Yvonne Wren

Jill Titterington

Paul White Paul.White@uwe.ac.uk
Professor in Applied Statistics



Abstract

Connected speech (CS) is an important component of child speech assessment in both clinical practice and research. There is debate in the literature regarding what size sample of CS is required to facilitate reliable measures of speech output. The aim of this study was to identify the minimum number of word tokens required to obtain a reliable measure of CS across a range of measures. Participants were 776 5-year-olds from a longitudinal community population cohort study (Avon Longitudinal Study of Parents and Children, ALSPAC). Children’s narratives from a story retell task were audio-recorded and phonetically transcribed. Automatic analysis of the transcribed speech samples was completed using an automated transcription and analysis system. Measures of speech performance extracted included: a range of profiles of percentage consonant correct; frequency of substitutions, omissions, distortions and additions (SODA); percentage of syllable and stress pattern matches; and a measure of whole word complexity (Phonological Mean Length of Utterance, pMLU). Statistical analyses compared these measures at different CS sample sizes in increments using averages and weighted moving averages, and investigated how measures performed between CS samples grouped into word tokens of at least 50, 75 and 100, and restricted to samples of 50–74, 75–99 and 100–125. Key findings showed that sample sizes of 75 word tokens and above showed minimal differences in most measures of speech output, suggesting that the minimum requirement for samples of CS is a word count of 75. The exception to this is in the case of pMLU and measures of substitutions and distortions when a word count of 100 is recommended.

Citation

Wren, Y., Titterington, J., & White, P. (2021). How many words make a sample? Determining the minimum number of word tokens needed in connected speech samples for child speech assessment. Clinical Linguistics & Phonetics, 35(8), 761-778. https://doi.org/10.1080/02699206.2020.1827458

Journal Article Type Article
Acceptance Date Sep 20, 2020
Online Publication Date Oct 6, 2020
Publication Date 2021
Deposit Date Sep 20, 2020
Publicly Available Date Jul 21, 2021
Journal Clinical Linguistics & Phonetics.
Print ISSN 0269-9206
Electronic ISSN 1464-5076
Publisher Taylor & Francis
Peer Reviewed Peer Reviewed
Volume 35
Issue 8
Pages 761-778
DOI https://doi.org/10.1080/02699206.2020.1827458
Keywords Speech, transcription, speech Sound Disorder, alspac, connected speech, sample size
Public URL https://uwe-repository.worktribe.com/output/6698613
Additional Information From: Clinical Linguistics & Phonetics
Sent: Sunday, September 20, 2020 9:32:40 AM
To: Yvonne Wren
Subject: Clinical Linguistics & Phonetics - Decision on Manuscript ID TCLP-2020-0090.R1

20-Sep-2020

Dear Dr Wren:

Ref: How many words make a sample? Determining the minimum number of word tokens needed in connected speech samples for child speech assessment

Our referees have now considered your paper and have recommended publication in Clinical Linguistics & Phonetics. We are pleased to accept your paper in its current form which will now be forwarded to the publisher for copy editing and typesetting.

Accepted papers will be transmitted for production. The first and most important task for authors at that point will be to complete an online author agreement form. Please make sure you complete it as soon as you receive the publisher notice about it.

You will receive proofs for checking. The publisher requests that proofs are checked and returned within 48 hours of receipt.

Thank you for your contribution to Clinical Linguistics & Phonetics and we look forward to receiving further submissions from you.


Sincerely,
Dr Nicole Müller
Editor in Chief, Clinical Linguistics & Phonetics
nicole.muller@ucc.ie

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